import numpy as np
import pandas as pd
from bokeh import plotting, io

from src.params import DEFAULTFORMAT as FMT
import src.choropleth as choro

FMT.update({'line_width':1, 'line_color':'black'})
choro.empty_map('state', FMT, output='png')

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Figure(

id = '1002', …)

above = [],

align = 'start',

aspect_ratio = None,

aspect_scale = 1,

background = None,

background_fill_alpha = {'value': 1.0},

background_fill_color = {'value': None},

below = [LinearAxis(id='1013', ...)],

border_fill_alpha = {'value': 1.0},

border_fill_color = {'value': None},

center = [Grid(id='1017', ...), Grid(id='1022', ...)],

css_classes = [],

disabled = False,

extra_x_ranges = {},

extra_y_ranges = {},

frame_height = None,

frame_width = None,

height = None,

height_policy = 'auto',

hidpi = True,

js_event_callbacks = {},

js_property_callbacks = {},

left = [LinearAxis(id='1018', ...)],

lod_factor = 10,

lod_interval = 300,

lod_threshold = 2000,

lod_timeout = 500,

margin = (0, 0, 0, 0),

match_aspect = False,

max_height = None,

max_width = None,

min_border = 5,

min_border_bottom = None,

min_border_left = None,

min_border_right = None,

min_border_top = None,

min_height = None,

min_width = None,

name = None,

outline_line_alpha = {'value': 1.0},

outline_line_cap = 'butt',

outline_line_color = {'value': None},

outline_line_dash = [],

outline_line_dash_offset = 0,

outline_line_join = 'bevel',

outline_line_width = {'value': 1},

output_backend = 'canvas',

plot_height = 600,

plot_width = 1000,

renderers = [GlyphRenderer(id='1037', ...)],

right = [],

sizing_mode = None,

subscribed_events = [],

tags = [],

title = Title(id='1003', ...),

title_location = 'above',

toolbar = Toolbar(id='1028', ...),

toolbar_location = 'right',

toolbar_sticky = True,

visible = True,

width = None,

width_policy = 'auto',

x_range = DataRange1d(id='1005', ...),

x_scale = LinearScale(id='1009', ...),

y_range = DataRange1d(id='1007', ...),

y_scale = LinearScale(id='1011', ...))

Load sample data

cmplx = pd.read_csv('data/test/fitness_county_new.csv', dtype={'fipstext':str})
supp = pd.read_csv('data/test/cbp_suppression_2016_EMP.csv', dtype={'GEO.id2':str})

Divergent data

no customization

p = choro.choropleth_county(supp, 'GEO.id2', 'fips', 'resid', 'divergent', state_outline='None', output='png')

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fmt = {'background_color':'#d1d1d1', ## add background color
       'line_width':0.5, 'line_color':'#d3d3d3', ## change county line width and color
       'fill_alpha':0.8, ## change opaqueness of color
       'cbar_textfmt':"0.00", 'cbar_max':0.25, 'cbar_min':-0.25} ## change colorbar formatting

p = choro.choropleth_county(supp, 'GEO.id2', 'fips', 'resid', 'divergent', state_outline=None, formatting=fmt, output='svg')

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Note: cannot export multi-layer (with state_outline) as svg; either export as png or export single layer and empty map to be combined in Illustrator or other svg editing program

change palette, simplify shape, add state outline

fmt = {'st_fill':None, 'line_width':0.5, 'palette':2, 'line_color':'#d3d3d3', 
       'cbar_textfmt':"0.00", 'cbar_max':0.25, 'cbar_min':-0.25, 'fill_alpha':1, 
       'simplify':0.028, ## simplify geo shape
       'background_color':'darkgray'}

p = choro.choropleth_county(supp, 'GEO.id2', 'fips', 'resid', 'divergent', state_outline='after', 
                            formatting=fmt, output='png')

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show what it would look like with missing data: relies on background being different color from midpoint

supp_missing = supp.copy()
random = np.random.randint(1, len(supp), size=round(0.3*len(supp)))
supp_missing.iloc[random, 7] = np.nan

choro.choropleth_county(supp_missing, 'GEO.id2', 'fips', 'resid', 'divergent', state_outline='after', formatting=fmt, output='png')

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Sequential data

only MSAs (coded with the constituent counties), no additional formatting

p = choro.choropleth_county(cmplx, 'fipstext', 'fips', 'f_2016', 'sequential', output='png')

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Add formatting

fmt = {'simplify':0.028, ## simplify geojson shape
       'ncolors':7, 'palette':2, ## specify color palette and number of color breaks
       'wt':1200, 'ht':720, ## dimensions for interactive version (web browser)
       'background_color':None, 'line_color':'white', 'line_width':0.2, ## transparent background and soft white lines
       'st_fill':'#c8c8c8', 'st_alpha':1, 'st_line_width':1, ## color state to be gray and have thick lines
       'cbar_title':'Community Fitness', 'cbar_title_align':'center', ## add color bar title
       'cbar_tick_alpha':0, 'cbar_min':0, 'cbar_max':7, 'cbar_fontsize':"8pt", ## change color bar font, remove ticks
        }

p = choro.choropleth_county(cmplx, 'fipstext', 'fips', 'f_2016', 'sequential', state_outline='both', ## draw state outline before and after
                                formatting=fmt)

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could also output as bokeh to customize further

p = choro.choropleth_county(cmplx, 'fipstext', 'fips', 'f_2016', 'sequential', state_outline='before',
                                formatting=fmt, output='bokeh')

fmt2 = {'background_color':None, 'st_fill':None, 'st_alpha':0, 'st_line_width':1, 
        'simplify':0.028, 'st_line_color':'black'}
choro.draw_state(p, fmt2)

io.output_notebook()
plotting.show(p)
# io.output_file('cmplx_main.html')
# io.reset_output()

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